Narula Institute of Technology

About: Narula Institute of Technology is a based out in . It is known for research contribution in the topics: Quantum dot cellular automaton & Cognitive radio. The organization has 288 authors who have published 490 publications receiving 2258 citations. The organization is also known as: NiT.

Unit Commitment Solution by Branch and Bound Algorithm

Abstract: For a short period, to obtain a secured economic dispatch of power generation, Security Constrained Unit Commitment (SCUC) is programmed to commit the units by minimizing the operating costs while maintaining the balance between supply and demand in a deregulating environment. This paper discusses a vivid planning horizon of three and six periods distributed in a day taking into account the fixed cost, variable cost, start-up and shut-down cost, ramping up and down limits, minimum and maximum power bounds, spinning reserve constraints of the units and line load abilities which are all modelled to commit the generators in binary digits only. The proposed approach applies the Branch and Bound algorithm to test the system. The iterative process will converge, if the optimal solution exists. In this paper three and six bus systems are analyzed to prove the effectiveness of this model which can be extended for larger systems too.

Diagnoses of Melanoma Lesion Using YOLOv3

Abstract: The most modifiable risk factor for skin cancer is ultraviolet radiation (UVR) exposure. Melanoma or malignant melanoma is the rarest but at the same time deadliest form of skin cancer. While prevention of melanoma is possible to some extent by educating masses to involve in safe sun practices as avoiding sun exposure during peak radiation hours, using protective clothing, applying sunscreen and distancing oneself from artificial sources of UV light, early detection and accurate treatment of the disease may curtail the fatality of the deadly disease. If statistics are to be believed, the lifetime risk of developing melanoma in the year 1935 was 1 in 1500 as compared to 1 in 50 in 2010, indicating its dramatic increase in the last century. While effective and timely treatment of melanoma has been a subject of prime importance for researchers and the medical fraternity alike, several invasive and non-invasive techniques have come to the fore from time to time for diagnosis of melanoma. Analysis of the several methods developed during the years suggests that easier access to skin examinations increase the chances of accurate and well-timed detection of melanoma and computer-aided diagnosis (CAD) has played a major role in fulfilling the same. This work proposes a novel CAD approach which includes preprocessing of the dermoscopic images by Dull Razor algorithm followed by classification by deep learning-based algorithm ‘You Only Look Once’ (YOLO) and finally segmentation of the identified image by a self-designed algorithm. The experiments have been conducted on three publicly available datasets—PH2, ISBI 2017 and ISIC 2016. The combination of the total methodology offers a Jac score of 86.12% and Dic of 92.55% which is way superior to results of contemporary works in the area.

Threshold voltage roll-off for triple gate FinFET analysis based on several semiconductors used as substrate

Abstract: The literature of power device must aware of the fact of proper tradeoff between the choice of semiconductor material and the proper oxide along with it. With the growing semiconductor technology, the traditional semiconductor now has the promising competitors like silicon carbide and gallium nitride.The simulation considers the calculation of minimum potential at the center plane of the FinFET channel through which roll-off of threshold voltage is measured. The analysis proves gallium nitride and silicon carbide as the most promising material for FinFET manufacturing industries. The drain to source voltage along with fin-height, fin thickness and channel length are varied keeping other parameters constant. The purpose of this work is to find out the “other than silicon” material in solid state device technology.

A genetically trained neural network application for fault finding in antenna arrays

Abstract: In this work, an extension of the previous approach on the Genetic Algorithm based Backpropagation Network (GA/BPN) is presented for finding the positions of defective elements in antenna arrays. The backpropagation network (BPN) takes samples of radiation pattern of the array with fault elements and maps it to the location of the faulty element in that array. The weights were extracted and optimized using GA. The result of the conventional ANN procedure is compared with genetically trained neural network approach. The developed methodology is tested for a linear array. The developed network can be used at the base stations to find out the number and location of the fault elements in the array in space platforms.

Modified Gossip Protocol in Wireless Sensor Networks Using Chebyshev Distance and Fuzzy Logic

Abstract: The Flooding is a traditional flat based routing protocol where unlimited broadcasting of the packets in the flooding scheme will cause the huge energy consumption to send the packets from source to sink due to implosion, overlap, resource blindness and consequently creates broadcast storm. However Gossiping routing protocol in WSNs is very much effective due to its simplicity, robustness, distributed and capability to work in noisy and uncertain environments. But due to recirculation of information and repeated data communication of randomized gossip protocol which can lead to a significant energy consumption of the network. This paper proposes an energy efficient routing protocol based on Fuzzy Logic and Chebyshev Distance, which is a modification of gossip protocol. The new protocol determines the optimal routing path from source to destination by selected the best node from candidate nodes in the forwarding paths by favoring highest remaining energy and the lowest distance to the sink. Simulation results shows that the proposed method is efficient to control messages forwarding and improves the performance which minimizes the overall energy consumption and maximize WSNs lifespan.